lthibault

1. Install FSL using a compatible shell (bash or tcsh), using the usual method.
2. Copy fsl.fish to the appropriate location (usually /usr/local/fsl/etc/fslconf/).
3. Append the contents of config.fish to your own config.fish

amroamroamro

Python version of the MATLAB code in this Stack Overflow post: https://stackoverflow.com/a/18648210/97160

The example shows how to determine the best-fit plane/surface (1st or higher order polynomial) over a set of three-dimensional points.

Implemented in Python + NumPy + SciPy + matplotlib.

stephenparish

Commit Message Conventions

These rules are adopted from the AngularJS commit conventions.

• Goals
• Generating CHANGELOG.md
  • Recognizing unimportant commits
  • Provide more information when browsing the history
• Format of the commit message
• Subject line

mikofski

function [fx,fy] = polyDer2D(p,x,y,n,m)
%POLYDER2D Evaluate derivatives of 2-D polynomial using Horner's method.
%   F = POLYDER2D(P,X,Y,N,M) evaluates the derivatives of 2-D polynomial P at
%   the points specified by X and Y, which must have the same dimensions. The
%   outputs FX and FY will have the same dimensions as X and Y. N and M specify
%   the order of X and Y respectively. Polynomial coefficients are in the
%   following order.
%
%   F(X,Y) = P_1 * X^N * Y^M + P_2 * X^{N-1} * Y^M + ... + P_{N+1} * Y^M + ...
%            P_{N+2} * X^N * Y^{M-1} + P_{N+3} * X^{N-1} * Y^{M-1} + ... + P_{2*(N+1)} * Y^{M-1} + ...

pavanky

I have to be frank here, this is going to be

    - criticism of thrust
    - Showing off ArrayFire (of which I am a core developer)

*Criticism of thrust*

They do a good job at optimizing parallel algorithms for vector inputs. 
They use data level parallelism (among other things) to parllelize algorithms that work really well for large, vector inputs. 
But they fail to improve upon it and go all the way to perfom true data level parallelism. i.e. a large number of small problems.